/DDC

Code for dynamical differential covariance

Primary LanguageJupyter Notebook

Dynamical differential covariance (DDC)

Checkout the latest manuscript version through bioRxiv: https://www.biorxiv.org/content/10.1101/2021.06.18.448901v2.full.pdf+html
All scripts were carefully annotated. Below is a quick summary.

Connectivity estimation:

  • estimators.m: Common estimators including covariance <x,x>, Precision matrix, nonlinear averaging matrix <R(x),x>, dCov computed by symmetric difference quotient
  • dCov_numerical.m: dCov calculated by different numerical estimations of the time derivative
  • derivative_123.m: Supporting file for dCov_numerical.m
  • DDC calculation: matrix product of dCov and <x,x>^{-1} or <R(x),x>^{-1}

Network simulations:

  • Linear_simulation.m: simulation of linear stochastic systems
  • Nonlinear_simulation.m: simulation of nonlinear stochastic systems
  • LIF_network_YC.m: Leaky-integrate-and-Fire network simulation
  • simulate_reduced_wong_wang.ipynb: Reduced Wong-Wang simulation

Performance evaluation:

  • FC_GT_ROC.m: classification sensitivity for LIF network recovery
  • c_sensitivity_YC.m: c-sensitivity calculation

HCP dataset